In Figure REF , we see that ABI Band 13 in GOES, the clean infrared window 10.3 m band, gets the highest attribution. According to NOAA [1]}, this band is least sensitive to water vapor absorption than other infrared bands. It therefore improves atmospheric moisture corrections, aids in cloud and other atmospheric feature identification/classification. This shows that the model has learnt from features that conforms with our knowledge of what the most important GOES band should be. It is interesting to note that ABI Band 2, the Red Visible 0.64 m band, is important for the 1 hour forecast, but rapidly decreases in importance for even the 3 hour forecast, and has no significance to any of the longer hours. This could be due to the very fine resolution (0.5 km) of this band which allows detection of boundaries and small clouds making it useful for nowcasting. In contrast, ABI Band 3, the Veggie 0.86 textmugreek m band, has higher attribution for the longer range forecasts than for the 1 hr nowcast, implying that the land characteristics maybe an important feature predicting rain a few hours out. The Mid-level water vapour 6.9 textmugreek m band, ABI Band 9, is used for tracking middle tropospheric winds, monitoring severe weather potential, estimating mid-level moisture, and other purposes [2]}. That the prediction of MetNet-2 relies on this feature is another sanity check that the model is learning meaningful information.
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